Social network services (SNS) continue to become more and more popular in people's daily communication. People share ideas, activities, events, and interests using social communication tools such as MESSENGER, FACEBOOK, TWITTER, microblog, forum, etc. For East Asian languages, people use an IME (input method editor) to type text into the social network services. An input method editor is an operating system component or program that allows users to enter characters and symbols not found on their input device. An IME is a tool which converts the phonetic of a word, typed on a standard keyboard, into East Asian characters. For example, the most common method of typing Chinese is to enter pinyin directly, which the IME will then convert to characters. Pinyin is a system transcribing Chinese into English, wherein the sounds of Mandarin are represented using the western (Roman) alphabet. Thus, once the phonetic pinyin spelling is entered, the IME uses at least one dictionary and statistical language models to select a conversion results given the user's phonetic input. The dictionary and statistical language model is based on a collection of language text pieces representing the whole range of the target language in statistically unbiased manner, and which is selected according to external criteria to represent, as far as possible, the desired language to thereby cover the commonly used words and text. Unfortunately, IME does not adapt to the vocabulary that people often use in the SNS such as film or book names, domain terms, product names, and people names. Many of these words may be completely new. Thus, users may not get the expected words in their top IME candidate list. This presents a problem especially in social communication tools such as IM because users want to type fast and efficiently. In addition, users want suggestions about the words their community uses when they type part of the phonetic.
Currently to compensate, the IME learns the words frequently used by each user of the system and builds a personalized dictionary. However, as social communication becomes more and more popular, it is tedious for users to constantly add new terms to their own personal vocabulary. For example, when two users communicate, they each have their own personal IME dictionary. Thus, when a first user enters a new term, their personal vocabulary is updated so the IME will recognize the new term from then on. Yet, when the second person uses the same term in the communication thread, their IME converts the term incorrectly, thereby requiring correction of the conversion and updating their personal vocabulary.
Accordingly, there is a need for a system, method and computer-readable storage device for providing cloud-based shared vocabulary/typing history for efficient social communication.